一种改进的ESPRIT方法

提出一种改进型的ESPRIT算法,对传统ESPRIT算法作以改进,提高了ESPRIT方法的性能,在小信噪比、多信号源的情况下提高了算法的测角精度.通过计算机仿真对改进算法的效果作了验证,验证了算法的有效性.     

用于信号波达方向估计的共轭ESPRIT算法及其性能分析

针对阵列天线的波达方向估计问题,给出了一种新颖的ESPRIT算法--共轭ESPRIT算法(C-ESPRIT).此算法利用阵列单元输出信号的共轭信息,得到整个阵列输出的协方差矩阵,通过对此矩阵的特征分解,并构造运算矩阵,最终求得信号的波达方向.仿真实验表明,C-ESPRIT算法不仅克服了传统ESPRIT算法在阵列单元数与信源数相同时不能可靠测向的不足,并且对信号波达方向的分辨能力和测角精度也显著高于传统的ESPRIT算法,因此,C-ESPRIT算法具有更广泛的适应性和更优越的测向性能.     

一种改进的二维虚拟ESPRIT算法-虚拟波达方向矩阵法

二维虚拟ESPRIT算法对子阵列内部结构要求低,但在低信噪比环境下,其估计误差较大。提出一种改进的二维虚拟ESPRIT算法,该算法具有二维虚拟ESPRIT算法的优点,但在低信噪比条件下他的估计误差更小,算法运算量更低。计算机仿真实验表明了改进的二维虚拟ESPRIT算法的有效性。     

ESPRIT算法估计性能分析

波达方向估计(DOA)技术渐渐成为移动通信中研究的热点,而ESPRIT算法是一种典型算法。在对ESPRIT算法进行分析的基础上,介绍了几种ESPRIT算法,并从信噪比、阵元数等不同情况下对几种算法的性能进行了仿真分析。     

ISAR雷达ESPRIT成像算法的改进

应用ESPRIT算法能够很好地提高逆合成孔径雷达成像的分辨率，但是传统的ESPRIT算法运算量大，运算速度慢。本文把对ESPRIT算法的一些最新成果即ESPRIT的改进引入ISAR成像过程，经过试验证明它能有效改善雷达成像的速度。     

基于改进ESPRIT算法的波达方向估计

把经典的波达方向估计算法应用于均匀圆阵智能天线是一个重要的研究课题。通过预处理技术把均匀圆阵转换成虚拟均匀线阵,为了解决噪声造成信号子空间的扰动问题,提出了两种总体最小二乘ESPRIT（TLS—ESPRIT）;为把ESPRIT算法应用于均匀圆阵,引入了模式空间的ESPRIT算法。通过建立恰当的数学模型,对上述各算法的均匀线阵和均匀圆阵上的性能进行仿真和对比分析。仿真结果证明,两种改进的算法性能均好于基本的ESPRIT算法。     

未知接收机通道特性下的信号“空间特征”估计算法

该文用均匀线阵研究了未知接收机通道特性下信号“空间特征”“w=2π△sinθ/λ)的估计问题,利用均匀线阵的冗余结构,本文给出了基于信号子空间的ESPRIT－Like算法,得到了一个信号“空间特征”和通道特性的近似解,ESPRIT－Like算法对信号“空间特征”估计具有较好的稳健性;与B.Friedlander,V.C.Soon等人（1994）提出的其它迭代算法相比,ESPRIT－Like算法具有计算量小的优点,数值仿真结果证实了本文算法的有效性并评价了算法的性能。     

基于带通欠采样的脉冲超宽带信号重建算法性能研究

从脉冲超宽带(PPM-UWB)信号解调的角度, 该文探讨了PPM-UWB带通欠采样信号处理的信号重建算法, 并将零化滤波算法和ESPRIT算法进行了仿真对比。ESPRIT算法与零化滤波算法相比需要的最小带宽要求较大, 但是在同等带宽条件下, ESPRIT算法具有更好的抗噪声性能。      

OFDM系统载频偏移的ESPRIT方法估计

分析了OFDM系统信号模型与经典ESPRIT方法所要求的观测向量之间的相合之处，给出了利用经典ESPRIT算法估计OFDM系统载频偏移的方法。然后尝试使用了一种经典ESPRIT算法（TLS—ESPVaT）估计载波频率偏移，仿真结果表明使用该方法比类ESPRIT算法具有更高的估计精度，证明了使用经典ESPRIT方法估计栽波频率偏移的可行性与有效性。     

基于多级维纳滤波的卫星信号DOA盲估计研究

卫星信号的盲测向是使用阵列天线进行导航终端抗干扰的基础,为了解决该问题,文中利用每颗卫星对应C/A码的唯一性进行解扩,提高了卫星导航信号的信噪比,采用多级维纳滤波分解得到的信号子空间代替ESPRIT算法中特征分解得到的信号子空间,提出一种基于多级维纳滤波的ESPRIT算法来实现卫星导航信号测向的应用.仿真结果表明,该算法不但能够实现卫星导航弱信号的测向,而且能够降低ESPRIT算法的运算量,具有更好的稳健性和测向性能.     

一种改进的ESPRIT测向算法

ESPRIT测向算法需要预先知道来波的数目。本文对ESPRIT算法进行了改进。改进后的算法把对空间来波数目的估计和空间来波方向的估计有效地结合起来，从整体上减少了运算量，而没有降低测向性能。最后进行了计算机仿真。仿真结果表明，该算法切实可行，具有工程应用价值。     

数字调制通信信号载波频率估计算法

应用修正的ESPRIT算法估计6种数字调制通信信号的载波频率，并且和其他两种算法的性能作了比较。仿真表明，在中等信噪比条件下，ESPRIT算法对载波频率的估计具有均值精确、方差小的特点，表现出较好的实用性和较强的稳健性。     

Two-dimensional angle and polarization estimation using the ESPRITalgorithm

It is shown how the ESPRIT (estimation of signal parameters via rotational invariance techniques) algorithm may be used with a square array of crossed dipoles to estimate both the two-dimensional arrival angles and the polarization of incoming narrowband signals. The ESPRIT algorithm exploits the invariance properties of such an array so that both angle and polarization estimates may be computed. Some typical examples showing the use of this approach are presented     

Modified ESPRIT (M-ESPRIT) algorithm for time delay estimation in both any noise and any radar pulse context by a GPR radar

This paper presents M-ESPRIT, a modified version of the ESPRIT algorithm, for the purpose of time delay estimation of backscattered radar signals. The proposed algorithm takes both the transmitted pulse shape and any noise into account. It can process raw data from experimental device without the preprocessing which would be required with the conventional ESPRIT algorithm.     

Angle and polarization estimation using ESPRIT with a polarizationsensitive array

It is shown how estimation of signal parameters via rotational invariance techniques (ESPRIT) may be used to estimate both the arrival directions and the polarizations of incoming plane waves with a uniform linear array of crossed dipoles. The ESPRIT algorithm exploits the invariance properties of such an array so that both angle and polarization estimates may be computed. Some typical examples showing the use of this method are presented     

Unitary ESPRIT: how to obtain increased estimation accuracy with areduced computational burden

ESPRIT is a high-resolution signal parameter estimation technique based on the translational invariance structure of a sensor array. Previous ESPRIT algorithms do not use the fact that the operator representing the phase delays between the two subarrays is unitary. The authors present a simple and efficient method to constrain the estimated phase factors to the unit circle, if centro-symmetric array configurations are used. Unitary ESPRIT, the resulting closed-form algorithm, has an ESPRIT-like structure except for the fact that it is formulated in terms of real-valued computations throughout. Since the dimension of the matrices is not increased, this completely real-valued algorithm achieves a substantial reduction of the computational complexity. Furthermore, Unitary ESPRIT incorporates forward-backward averaging, leading to an improved performance compared to the standard ESPRIT algorithm, especially for correlated source signals. Like standard ESPRIT, Unitary ESPRIT offers an inexpensive possibility to reconstruct the impinging wavefronts (signal copy). These signal estimates are more accurate, since Unitary ESPRIT improves the underlying signal subspace estimates. Simulations confirm that, even for uncorrelated signals, the standard ESPRIT algorithm needs twice the number of snapshots to achieve a precision comparable to that of Unitary ESPRIT. Thus, Unitary ESPRIT provides increased estimation accuracy with a reduced computational burden     

共轭增强ESPRIT算法

提出了共轭增强ESPRIT（CA-ESPRIT）算法，利用阵列输出的延迟相关函数及其共轭形成伪阵列输出，从而得到伪协方差矩阵，对其进行特征分解，用ESPRIT算法得到波迭方向。仿真实验表明，新算法可对多于阵元数的信号进行测向，其测角精度和分辨能力优于ESPRIT算法，运行时间小于有相同阵列扩展能力的MUSIC—like算法。     

用于线阵三维SAR成像的二维快速ESPRIT算法

线阵3维SAR系统可实现对地面场景的3维成像,是近年来研究的热点。但受载机平台和硬件条件的限制,其切航迹向和沿航迹向的分辨率难以提高。为了改善2维分辨率,该文提出了一种用于线阵3维SAR成像的2维快速ESPRIT算法,首先结合盖式圆方法和ESPRIT算法估计出点目标在切航迹向和沿航迹向位置,并通过该文改进的基于区域生长的2维位置配对方法替代最小二乘法快速求得目标散射系数,实现线阵2维SAR切航迹向和沿航迹向超分辨成像。该算法具有分辨精度高、运算速度快、实时性能好等优点。仿真实验证明了其有效性。      

Multiple invariance ESPRIT

A subspace-fitting formulation of the ESPRIT problem is presented that provides a framework for extending the algorithm to exploit arrays with multiple invariances. In particular, a multiple invariance (MI) ESPRIT algorithm is developed and the asymptotic distribution of the estimates is obtained. Simulations are conducted to verify the analysis and to compare the performance of MI ESPRIT with that of several other approaches. The excellent quality of the MI ESPRIT estimates is explained by recent results which state that, under certain conditions, subspace-fitting methods of this type are asymptotically efficient